{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,8]],"date-time":"2024-09-08T04:59:01Z","timestamp":1725771541161},"reference-count":13,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,9,26]],"date-time":"2020-09-26T00:00:00Z","timestamp":1601078400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,9,26]],"date-time":"2020-09-26T00:00:00Z","timestamp":1601078400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,9,26]],"date-time":"2020-09-26T00:00:00Z","timestamp":1601078400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,9,26]]},"DOI":"10.1109\/igarss39084.2020.9324722","type":"proceedings-article","created":{"date-parts":[[2021,2,19]],"date-time":"2021-02-19T11:10:14Z","timestamp":1613733014000},"page":"2839-2842","source":"Crossref","is-referenced-by-count":2,"title":["Deep Learning for Automatic Recognition of Oil Production Related Objects based on High-Resolution Remote Sensing Imagery"],"prefix":"10.1109","author":[{"given":"Nannan","family":"Zhang","sequence":"first","affiliation":[{"name":"Research Institute of Petroleum Exploration & Development, PetroChina,Beijing,China,100080"}]},{"given":"Hang","family":"Zhao","sequence":"additional","affiliation":[{"name":"Research Institute of Petroleum Exploration & Development, PetroChina,Beijing,China,100080"}]},{"given":"Yang","family":"Liu","sequence":"additional","affiliation":[{"name":"Research Institute of Petroleum Exploration & Development, PetroChina,Beijing,China,100080"}]},{"given":"Song","family":"Liu","sequence":"additional","affiliation":[{"name":"Research Institute of Petroleum Exploration & Development, PetroChina,Beijing,China,100080"}]},{"given":"Zhiguo","family":"Ma","sequence":"additional","affiliation":[{"name":"Research Institute of Petroleum Exploration & Development, PetroChina,Beijing,China,100080"}]},{"given":"Hongyan","family":"Guo","sequence":"additional","affiliation":[{"name":"Research Institute of Petroleum Exploration & Development, PetroChina,Beijing,China,100080"}]},{"given":"Wentong","family":"Dong","sequence":"additional","affiliation":[{"name":"Research Institute of Petroleum Exploration & Development, PetroChina,Beijing,China,100080"}]},{"given":"Hongying","family":"Zhou","sequence":"additional","affiliation":[{"name":"Research Institute of Petroleum Exploration & Development, PetroChina,Beijing,China,100080"}]},{"given":"Zhongyong","family":"Sun","sequence":"additional","affiliation":[{"name":"Research Institute of Petroleum Exploration & Development, PetroChina,Beijing,China,100080"}]},{"given":"Kaijun","family":"Qian","sequence":"additional","affiliation":[{"name":"Research Institute of Petroleum Exploration & Development, PetroChina,Beijing,China,100080"}]}],"member":"263","reference":[{"key":"ref10","first-page":"91","article-title":"Faster RCNN: Towards real-time object detection with region proposal networks","author":"ren","year":"2015","journal-title":"In Advances in Neural Information Processing Systems"},{"journal-title":"Speed\/accuracy trade-offs for modern convolutional object detectors","year":"2017","author":"huang","key":"ref11"},{"key":"ref12","first-page":"1440","author":"girshick","year":"2015","journal-title":"Fast r-cnn in Proceedings of the IEEE International conference on Computer Vision"},{"key":"ref13","article-title":"Tensorflow: Large-scale machine learning on heterogeneous systems","author":"abadi","year":"2015","journal-title":"software available from tensorflow org"},{"journal-title":"Recent advances in deep learning for object detection","year":"2019","author":"wu","key":"ref4"},{"journal-title":"A Comprehensive Survey of Deep Learning in Remote Sensing Theories Tools and Challenges for the Community","year":"2017","author":"ball","key":"ref3"},{"journal-title":"Deep learning for generic object detection A survey","year":"2019","author":"liu","key":"ref6"},{"journal-title":"Object Detection in 20 Years A Survey","year":"2019","author":"zou","key":"ref5"},{"journal-title":"Deep learning in remote sensing A review","year":"2017","author":"zhu","key":"ref8"},{"journal-title":"A Survey o f Deep Learning-based Object Detection","year":"2019","author":"jiao","key":"ref7"},{"key":"ref2","first-page":"697","article-title":"Recognition of Oil Contaminated Waster Water uses Landsat8 Imagery","author":"liu","year":"2016","journal-title":"IEEE International Geoscience and Remote Sensing Symposium"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/IGARSS.2018.8518054"},{"key":"ref9","first-page":"1097","article-title":"ImageNet Classification with Deep Convolutional Neural Networks","author":"krizhevsky","year":"2012","journal-title":"Advances in neural information processing systems"}],"event":{"name":"IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium","start":{"date-parts":[[2020,9,26]]},"location":"Waikoloa, HI, USA","end":{"date-parts":[[2020,10,2]]}},"container-title":["IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9323073\/9323063\/09324722.pdf?arnumber=9324722","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T21:52:45Z","timestamp":1656453165000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9324722\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9,26]]},"references-count":13,"URL":"https:\/\/doi.org\/10.1109\/igarss39084.2020.9324722","relation":{},"subject":[],"published":{"date-parts":[[2020,9,26]]}}}